Optimization of social media engagement

ABSTRACT

Methods for optimizing social media are disclosed. Such methods may include identifying at least one keyword utilized for at least one webpage, identifying social media correspondence referencing the at least one keyword, analyzing content collected from the social media to determine a frequency of references to the at least one keyword and generating at least one report including information based on the analysis. The report may include recommendations for optimizing social media by, for example, increasing visibility by using high-performing keywords. Systems for performing the methods are also disclosed.

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application claims priority to U.S. Provisional PatentApplication No. 61/449,064, filed Mar. 3, 2011, and to U.S. ProvisionalPatent Application No. 61/549,060, filed Oct. 19, 2011, each of whichdocuments is incorporated herein by reference.

TECHNICAL FIELD

Technologies described herein related generally to social media and,more particularly, to methods and systems for optimizing social mediaengagement.

BACKGROUND

Social media websites are becoming increasingly popular by having theabilities of connecting users and communities in a collaborative way.Social media services explore the opportunities for advancedcommunication and also serve as an advanced content sharing mechanism.Examples include not only social networking services (SNSs), such asMYSPACE and FACEBOOK, but also telecom operator's services such asmessaging, photo-sharing, person-to-person as well as conference callsand even microblogging services such as TWITTER.

Millions of users are actively using services provided by such socialmedia websites, exposing new trends in communication and content sharingthat has not been typical in the past. For example, TWITTER has over 100million active users generating over 250 million tweets per day (20percent of which contain links). Thus, social media websites such asTWITTER, offer an attractive channel for online marketing and sales.

The overwhelming quantity of information available from social mediawebsites creates challenges in effectively using such information inmarketing strategies. Conventional social media analysis has focused onbrand monitoring and reputation management on such social mediawebsites. It would be desirable to provide methods and systems forexploring ways to drive acquisitions through social media websites.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential characteristics of the claimed subject matter, nor is itintended to be used as an aid in determining the scope of the claimedsubject matter.

Technologies described herein relate generally to methods for optimizingsocial media engagement. In some embodiments, such methods may includeidentifying one or more search engine optimization keywords utilized forone or more webpages and identifying social media correspondencereferencing the one or more search engine optimization keywords. Themethod may further include recommending material related to the webpagesthat contain the search engine optimization keywords referenced in thesocial media correspondence for engagement in the social media.

In other embodiments, such methods may include collecting content from aplurality of webpages by crawling at least one network, searching thecontent collected from the plurality of webpages to identify referencesto at least one keyword, analyzing the content to determine a frequencyof the references to the at least one keyword associated with at leastone of the plurality of webpages, the relevant references generated byusers of social media and generating at least one report for display,the report comprising information based on the content.

Technologies described herein relate generally to systems for optimizingsocial media. Such a system may include, for example, a deep indexengine configured to crawl a plurality of webpages and to identifysocial media correspondence located on the plurality of webpages, ananalyzing module configured to analyze the social media correspondenceto identify references to at least one keyword in the social mediacorrespondence and to create at least one report based on the referencesto the at least one keyword and a reporting module for generating atleast one report for display to a user, the report comprisinginformation based on the analysis of the social media.

These and other aspects of example embodiments of the invention willbecome more fully apparent from the following description and appendedclaims.

BRIEF DESCRIPTION OF THE DRAWINGS

To further clarify various aspects of some embodiments of the presentinvention, a more particular description of the invention will berendered by reference to specific embodiments thereof that areillustrated in the appended drawings. It is appreciated that thesedrawings depict only typical embodiments of the invention and aretherefore not to be considered limiting of its scope. The invention willbe described and explained with additional specificity and detailthrough the use of the accompanying drawings:

FIG. 1A illustrates an embodiment of a social media engagement system inaccordance with the technologies described herein;

FIG. 1B illustrates another embodiment of a social media engagementsystem in accordance with the technologies described herein;

FIG. 2 is a flow type diagram illustrating an embodiment of a method ofincreasing social media engagement in accordance with the technologiesdescribed herein; and

FIG. 3 illustrates an embodiment of a computing system that canimplement some embodiments described herein.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented herein. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations, all of which areexplicitly contemplated herein.

With the rise in the wide spread use of social media and its integrationinto the daily lives of internet users, companies and individuals (e.g.,“entities”) are realizing the benefits that may be achieved by usingsocial media in their marketing strategies. As entities turn to socialmedia, it may be desirable to be able to identify when social mediacorrespondence relates to content on the entities' webpages. It mayfurther be desirable to provide the ability to engage in the socialmedia correspondence using the content from the entities' webpages.

Accordingly, embodiments disclosed herein generally relate to computingsystems and computing processes used in methods of optimizing socialmedia engagement by tracking and engaging in social mediacorrespondence. By engaging in social media correspondence, an entitycan achieve greater brand visibility. Furthermore, engaging in socialmedia correspondence can lead to increased traffic of an entity's mainwebpage and better page rank for the entity's webpage.

Reference will now be made to the figures wherein like structures willbe provided with like reference designations. It is understood that thefigures are diagrammatic and schematic representations of someembodiments of the invention, and are not limiting of the presentinvention, nor are they necessarily drawn to scale.

FIG. 1A illustrates an embodiment of a social media optimization system100 a, which can include a network 102. In some embodiments, the network102 can be used to connect the various parts of the system 100 a to oneanother, such as between a web server 106, a deep index engine 108, acorrelator 104, and a social media optimization module 112. It will beappreciated that while these components are shown as separate, thecomponents may be combined as desired. Further, while one of eachcomponent is illustrated, the system 100 a may optionally include anynumber of each of the illustrated components.

The network 102 may include the Internet, including a globalinternetwork formed by logical and physical connections between multiplewide area networks and/or local area networks and can optionally includethe World Wide Web (“Web”), including a system of interlinked hypertextdocuments accessed via the Internet. Alternately or additionally, thenetwork 102 includes one or more cellular RF networks and/or one or morewired and/or wireless networks such as, but not limited to, 802.xxnetworks, Bluetooth access points, wireless access points, IP-basednetworks, or the like. The network 102 can also include servers thatenable one type of network to interface with another type of network.

The web server 106 can include any system capable of storing andtransmitting a webpage to a user. The web server 106 can provide accessto the webpages of a website to be analyzed for improving social mediaoptimization. For example, the web server 106 can include a computerprogram that is responsible for accepting requests from clients (useragents such as web browsers), and serving them HTTP responses along withoptional data contents, which can include HTML documents and linkedobjects for display to the user. Additionally or alternately, the webserver 106 can include the capability of logging some detailedinformation, about client requests and server response, to log files.

The website can include any number of webpages. The aggregation ofreferences to the various webpages can be referred to as traffic. Itshould be noted that the term webpage, as used herein, refers to anyonline posting, including domains, subdomains, web posts, UniformResource Identifiers (“URIs”), Uniform Resource Locators (“URLs”),images, videos, or other piece of content and non-permanent postingssuch as e-mail and chat, unless otherwise specified.

In some embodiments, the deep index engine 108 may be configured tocrawl the webpages accessed by the webserver 106 to retrieve externaldata. As used herein, terms “crawl” and “crawling” may refer tocollecting content of multiple files or sites (e.g., webpages) on thenetwork 102 so that the content may be searched. In particular, the deepindex engine 108 may be configured to crawl the webpages and analyzedata associated with the crawl, including on-page information and backlink data (e.g., back link URL, anchor text, etc.) for each webpage. Thedeep index engine 108 may be configured to crawl webpages via theInternet and/or via a wireless network. Social media is often accessedusing a mobile device (e.g., a mobile phone, a personal digitalassistant (PDA), a tablet computer, etc.) through the wireless network.The deep index engine 108 may utilize an algorithm or software mechanism(e.g., a crawler) to crawl the files or sites on the network 102 for thecontent.

Thus, the webpages crawled by the deep index engine 108 through thewireless network may provide user-specific and/or location-specificinformation. A deep index engine 108 according to some embodiments isdescribed in more detail in copending U.S. patent application Ser. No.12/436,704 entitled COLLECTING AND SCORING ONLINE REFERENCES, filed May6, 2009, which application is hereby incorporated by reference in itsentirety. The functionalities described herein can be applied tooptimizing webpages for a website.

A correlator 104 according to some embodiments is described in moredetail in co-pending U.S. patent application Ser. No. 12/574,069, filedOct. 6, 2009 entitled CORRELATING WEB PAGE VISITS AND CONVERSIONS WITHEXTERNAL REFERENCES, which application is hereby incorporated byreference in its entirety. The functionalities described herein can beapplied to optimizing webpages for a website.

The correlator 104 or other component may be configured to collect webanalytics data from the webpages. The web analytics data may be used inestimating the cost, value, or both, associated with one or more searchengine optimization (SEO) or social media optimization opportunities.Examples of web analytics data that may be collected include number ofvisitors, page views, conversions (e.g., purchases), and the like or anycombination thereof.

The social media optimization module 112 is configured for tracking,identifying, and analyzing social media correspondence as well asorchestrating and performing the webpage analysis of a website asdescribed herein so that recommendations can be made to improve socialmedia interactions and increase the exposure of the entity to therebyimprove the SEO of the website. The social media optimization module 112may access the social media correspondence generated with a user device(e.g., a computer or a mobile phone) in communication with the network112. The social media optimization module 112 is described in moredetail herein.

FIG. 1B illustrates another embodiment of a social media optimizationsystem 100 b. As shown, the network 102 operably couples the socialmedia optimization module 112 with a website computing system 128. Thesocial media optimization module 112 includes a computing system 120configured to perform social media optimization analysis and producerecommendations as described herein. The computing system 120 caninclude submodules for implementing particular functionalities. Thecomputing system 120 can be generic to and include an analytic module122, determination module 124, and a reporting module 126.

The website computing system 128 can include a website database 129 thatincludes SEO data from entity webpages 132 from an entity website 130.The entity website 130 can be the website of an entity for which socialmedia optimization is to be performed. The website database 129 canfurther include social media webpages 142 of a social media website 140.The social media website 140 can be any type of social media. Forexample, social media can include collaborative projects (e.g.WIKIPEDIA), blogs and microblogs (e.g. TWITTER), content communities(e.g. YOUTUBE), social networking sites (e.g. Facebook, virtual gameworlds (e.g. WORLD OF WARCRAFT), and virtual social worlds (e.g. SECONDLIFE), among other types of social media and can take many differentforms including Internet forums, weblogs, microblogging, social blogs,wikis, podcasts, photographs or pictures, video, rating, socialbookmarking, and others. The social media webpages 142 can include anytype of digital content that contains social media from the social mediawebsite 140.

For example, if the social media website 140 is a microblog ormicroblogging site, for example, TWITTER, the social media webpage 142may include a single micropost, a home page of a user with a microblogaccount with a collection of the user's microposts, or any other digitalcontent that contains microposts.

A micropost may include a message or post made public on a website ordistributed to a specific group of subscribers, who can observe themover the network 102 via, for example, a computer or a mobile device.Such microposts may be, for example, a status update, a comment, a post(e.g., a website address) or a so-called “check in” at a particularlocation via social media. Such a micropost on Twitter® socialnetworking service is often referred to as a “Tweet®.” Users may copyand repost the tweet of another, which is often referred to as a“retweet.” The micropost may include one or more so-called “hashtags,”in which the “#” symbol is used to mark words or topics in a Tweet®. Themicropost may also be a reply, such as another Tweet, in response to anoriginal Tweet, which is often denoted with the “@” symbol and ausername.

For customers looking to generate direct revenue, Tweets may be used todrive referral traffic and conversions from Twitter. However, this maybe challenging for customers because it may require customers toidentify high-value opportunities and respond very rapidly withrelevant, compelling tweets and content.

As another example, if the social media website 140 is a socialnetworking site, for example, FACEBOOK, the social media webpage 142 canbe a networking page of a user, a post of a user, a comment, or anyother digital content related to the social networking site.Additionally or alternatively, the website computing system 128 cancontain a second website database so that the entity webpages 132 andthe social media webpages 142 reside in separate databases. It should beunderstood that the data from the entity webpages 132 and the socialmedia webpages 142 may be stored in any configuration without departingfrom the embodiments described herein.

The website computing system 128 can obtain data from the entitywebpages 132 and the social media webpages 142 by accessing the entitywebsite 130 and the social media website 140 through a web server, suchas the web server 106 of FIG. 1A. Furthermore, the data from the entitywebpages 132 and the social media webpages 142 can be collected bycrawling the webpages 132, 142. In some embodiments, the webpages 132,142 can be crawled using the deep index engine 108 of FIG. 1A, forinstance. In some embodiments, the webpages 132, 142 can be crawledusing a different mechanism.

The data may be obtained from the webpages 132, 142 during apredetermined aggregation period. For example, the predeterminedaggregation period may be a time period, such as, one or more hours,days or weeks. As a non-limiting example, the data may be obtainedduring a single day or a single week.

In some embodiments, the website computing system 128 may conduct akeyword volume count in which each occurrence of the keyword is countedto determine keyword volume. The keyword volume may include a count ornumber of an exact and/or phrase match occurrence of the keyword in asocial media correspondence, such as a Tweet. The occurrence of thekeyword may be classified by according to a type of social mediacorrespondence in which they appear.

In embodiments in which the social media correspondence is obtained fromsocial media (e.g., TWITTER), each occurrence of the keyword may beclassified as a reposting of correspondence posted by another (e.g., aretweet), a reply to correspondence (e.g., a TWEET) posted by another oran original correspondence (e.g., a TWEET). The keyword occurrencesmarked as a specific user-defined topic (e.g., by the “#” symbol) ormarked by a username (e.g., by the “@” symbol) may count towards anumber of mentions metric.

One or more keyword trends may be determined based on the keywordvolume. Keyword trend strength may be calculated is calculated from apercent difference between the keyword volume and an average volume forthe keyword over a predetermined time period (e.g., the aggregationperiod). As a non-limiting example, the aggregation period may be oneday and the keyword trend strength may include a percent deviation froman average determined over another predetermined time period (e.g., 7days). As another non-limiting example, the aggregation period may beone week and the keyword trend strength may include a percent deviationfrom an average determined over another predetermined time period (e.g.,4 weeks).

The website computing module 128 may additionally filter data from theentity webpages 132 and the social media webpages 142. The data may befiltered based on any relevant criteria, such as, a number of webpagesor a period of time. As a non-limiting example, a sample size may beselected including a predetermined number of webpages and the websitecomputing module 128 may be configured to obtain information from asample of entity webpages 132 and/or the social media webpages 142according to the relevant sample size. Thus, rather than obtaining datafrom each webpage including the SEO keyword input by a third party, thedata may be filtered to include a particular number or percentage ofwebpages, or to include one or more websites of interest. The sample mayfrom the entity webpages 132 and the social media webpages 142 may beused to determine a frequency of SEO keyword. Using the filtered data,the frequency at which the SEO keyword occurs in webpages (e.g., theentity webpages 132 and the social media webpages 142) may be estimated.For example, if the sample size is fifty (50) percent of the webpages,the number of references to the SEO keyword appearing in the webpagesobtained from the sample may be doubled to provide an estimate of theactual number of references to the SEO keyword. If the data obtainedfrom the sample indicates a low number of references to the keyword, orno references to the keyword, a larger sample size may be selected orthe filter may be removed to ensure accuracy of the estimate.

As another non-limiting example, the data may be filtered based onpredetermined period of time. A period of time may be selected and thenumber of references to the SEO keyword that appear on the webpagesduring the period of time may be determined. Thus, the frequency ofreferences to the SEO keyword during the predetermined period of timemay be determined.

The filtering criteria may be dynamically changed based on theinformation collected. For example, the group of webpages crawled overthe period of time, or the SEO keywords may be modified, as additionalinformation is gathered and analyzed. Furthermore, filtering data may beused to estimate the frequency of references to the SEO keywordsappearing on webpages, to determine the frequency of references to SEOkeywords appearing on the webpages in a predetermined period of time,and/or to determine a frequency of references to the SEO keywordsappearing on a predetermined group of webpages. Because businesses maybe charged a fee per each of the SEO keywords they select, filtering thedata is useful in providing such businesses with an estimate ofpotential costs associated with such services.

Referring again to the computing module 120, the analytic module 122within the computing module 120 can be configured to analyze thewebpages 132, 142 to obtain data from the webpage 132, 142. The analyticmodule 122 can include one or more algorithms for analyzing the webpages132, 142. In some embodiments, the analytic module 122 can analyzeon-page data, source code, or any other data of the entity webpages 132to identify SEO keywords, which may include any branded names of theentity or other words or string of words that are associated with theentity, product names produced by the entity, product categories,relevant search terms, general topics, and other words or strings ofwords used in SEO.

In some embodiments, the analytic module 122 can analyze on-page data,source code, or any other data of the social media webpages 142 toidentify social media correspondence. Social media correspondence can beany data placed on the social media webpages 142 by a user of the socialmedia website 140 that can be read by other users of the social mediawebsite 140. For example, in some embodiments, social mediacorrespondence can include posts, comments, or both on a socialnetworking website. In some embodiments, social media correspondence caninclude posts, comments, or both on a blog or microblog. It should beunderstood that the aforementioned are only some examples of differenttypes of social correspondence and that the scope of social mediacorrespondence as used herein should not be limited in anyway by theseexamples.

Additionally or alternatively, after the analytic module 122 identifiesthe social media correspondence located on the social media webpages142, the analytic module 122 can further analyze the social mediacorrespondence for one or more words, phrases, or other data using oneor more algorithms. For example, in some embodiments, the analyticmodule 122 can analyze the social media correspondence to identify theSEO keywords identified by the analytic module 122 in the entitywebpages 132.

Additionally or alternatively, the analytic module 122 can analyze theon-page data, source data, or both of the social media webpages 142and/or the social media website 140 to identify information aboutspecific users of the social media website 140. The identifiedinformation can include the social media participation of a user as wellas content provided or discussed by the user. The social mediaparticipation of the user can include how often the user participates inthe social media, such as the number of social media correspondencesproduced by the user. Additionally or alternately, the social mediaparticipation of the user can include how many other users of the socialmedia follow, view, comment on, reference, contribute to, or otherwiseacknowledge the social media correspondence produced by the user. Theanalysis may enable preparation of recommendations to improve visibilityby using high-performing keywords (e.g., keywords with a higher thanaverage number of references and/or providing a higher than averagereturn on investment). For example, the analysis of keyword trends maybe utilized to provide information about valuable keywords trending onsocial media, and to show how individual webpages rank and convert onthe high-performing keywords, to provide alerts on opportunities todrive engagement on social using existing content, and to prioritizewhich social media opportunities will be most effective if pursued. Therecommendations may further include one or more webpages determined tobe relevant for targeting consumers identified as interested in thespecific keywords. For example, consumers interested in the selectedkeywords may be identified and a determination may be made as to whichwebpages will be the best to use for targeting those consumers based onthe selected keywords. Such webpages may be identified based on ananalysis of rankings obtained from one or more search engines, an amountor type of traffic, conversions, bounce rate, conversion rate andrevenues. As a non-limiting example, the recommendation may includewebpages determined to be well-ranked and/or to have a higher thanaverage number of visits or conversions.

Some embodiments further relate to analytics and/or the generation ofanalytics related to the identification of social media correspondenceand SEO keywords. The analytics may be derived from the informationreceived from or collected from the webpages 132, 142. Such informationmay also be used for targeted marketing across platforms. Theinformation can also be used to generate revenue. The information may beused to target specific advertisements to specific consumers. Inaddition, demographics such as demographics of consumers (whenprovided), types of devices, types of content, and the like may becollected and used to generate analytics.

The information may also be used to determine a value of the SEOkeywords or the webpages 132, 142 and/or to rank the SEO keywords or thewebpages 132, 142. For example, information indicating that the SEOkeywords are references in social media correspondence more frequentlythan other SEO keywords is information that may be used by to rank therelevance of the SEO keywords and/or the webpages 132, 142. Morefrequently referenced SEO keywords may be ranked higher than other lessreferenced SEO keywords. The webpages 132, 142 referencing a particularSEO keyword of interest more frequently than other webpages may beranked higher than the other webpages. This information may also beused, for example, to predict or determine price points for social mediaengagement.

In another example, the analytics may be used to predict which SEOkeywords are more likely to be referenced in social media and/or whichwebpages are most likely to include the references to the SEO keywords.

The analytics may also be used to determine the SEO keywords thatprovide the highest return on investment (ROI). As used therein, theterm “return on investment” may refer to revenue generated from the SEOkeywords or popularity of the keywords in comparison to the costsassociated with use of the SEO keywords.

Additionally, one or more webpages having the highest number ofreferences to the SEO keyword may also be determined. For example, thewebpages may be sorted in the order of the frequency of keywordsassociated with the social media. The webpages including the highestnumber of references to the SEO keyword may be determined and thosewebpages may be targeted and optimized. In identifying the most relevantSEO keywords in the social media and the webpages most relevant toparticular SEO keywords, the social media optimization system 100 bdescribed herein enables tailoring of marketing strategies to optimizeSEO keyword usage.

The determination module 124 may also be configured to determine one ormore webpages that are being shared in social media regardless of theSEO keywords. Information related to such webpages may be analyzed todetermine the SEO keywords associated therewith and to optimize socialmedia correspondence.

The determination module 124 can obtain data from the analytic module122 and use the data to determine which identified social mediacorrespondences contain the SEO keywords identified in the entity'swebpages 132. The determination module 124 can include one or morealgorithms for processing the data obtained from the analytic module122. Additionally or alternately, the determination module 124 candetermine the frequency that the SEO keywords from the entity's website132 appear in the identified social media correspondences and rank theSEO keywords accordingly. Additionally or alternately, the determinationmodule 124 can determine if there is an increase in use of one or moreof the identified SEO keywords over a period.

Additionally or alternately, the determination module 124 can determinea rank of the social media participation of a user of the social mediawebsite 140 with respect to other users of the social media website 140.For example, for a microblog, such as TWITTER, the number of followers,retweets, and views of a user's TWEET can be used to rank a user ascompared to all other users of TWITTER. Additionally or alternately, thedetermination module 124 can also determine the rank of the social mediaparticipation of a user employing other factors, such as by usinginfluence and participation rankings produced by other websites orentities. Additionally or alternately, the determination module 124 candetermine which users of the social media website 140 are discussing,providing, viewing, or otherwise associating with social mediacorrespondence that relates to the identified SEO keywords.

The reporting module 126 can compile information from the analyticmodule 122, determination module 124, or both to generate various typesof reports and make recommendations to improve social mediaoptimization. The reporting module 126 can include one or morealgorithms that can generate one or more reports and provide one or morerecommendations for improved social media optimization.

The determination module 124 may access data from one or more mobiledevices via a wireless network to gather information and can generatemarketing information based on location. For example, location taggingon social media correspondence or login/check-in information provided insocial media correspondence may be analyzed to determine references tokeywords based on location.

The determination module 124 may analyze trends associated with the SEOkeywords, such as growth in social media correspondence and demographics(e.g., gender, race, age, interests, education, employment status, andlocation), consumption and creation of content. The information obtainedfrom such analysis may be provided, for example, in a report, anelectronic report and/or an electronic notification, and may be used totailor marketing strategies. The electronic report may be, for example,displayed on the screen of a computer, downloaded into one or moreelectronic file formats or printed onto paper.

Such reports generated based on the collected information may include,for example, activity reports, stimulus reports, dynamic maps, etc. Thereports may include information related to the webpages, the SEOkeywords, the social media, or users of the social media. As anon-limiting example, such a report may include a dynamic map ofactivity associated with the SEO keywords or with webpages including atleast one reference to the SEO keyword. As another non-limiting example,such a report may include an analysis of the webpages according to thereferences to the SEO keyword (e.g., webpages with the highest number ofoccurrences). As yet another non-limiting example, such a report mayinclude demographic information about the users associated with thereferences to the SEO keyword.

For example, an all keywords report may be generated that enables usersto quickly observe what keywords and webpages may most effectively driverevenue. Such keywords may be those with the highest number ofreferences in social media or may be those with the greatest increase inreferences within a predetermined time period. The all keywords reportmay additionally provide information about which keywords within a groupof multiple keyword groups (e.g. multiple product categories) areincreasing in social media correspondence. Such webpages may be thosethat include the highest number of references to one or more selectedkeywords or may be those in which the frequency of references to theselected keywords is increasing most rapidly. As a non-limiting example,the report may provide information related to the keywords and webpagesto include in social media correspondences, such as a TWEET made by auser of TWITTER, to drive revenue. For example, the report may provideinformation about the strongest trending keywords and the high-valuepages and opportunities related to those keywords. The all keywordsreport may include, for example, a stack bar-chart showing total keywordvolume by keyword trend strength.

The reports may be customized according to customer specifications. Forexample, the reports may be customized to include keywords with 0percent or less deviation from average, keywords trending above 0percent but less that 50 percent above average, keywords trending above50 percent but less that 100 percent from average, and/or keywordstrending 100 percent or more above average. The reports may include datafrom any number of aggregation periods.

As a non-limiting example, the report may be an electronic reportincluding web-based graphical user interfaces, or screens, in which thedata may be viewed. The electronic report may include one or morebuttons that links to a map of each trend strength category. When any ofthe buttons is selected, the keyword data may be filtered. For example,wherein the data may be filtered or sorted to show only the keywordsthat fall in the specific trend category described by the button.

The reports may include any number of fields, each of which may berelated to the keyword or to the social media. As non-limiting examples,the fields may include the keywords having the highest volume (e.g.,keyword rank), the webpages having the highest number of references tothe keyword (e.g., top ranked webpages), organic search revenue for thekeyword during a predetermined time period, and/or a percent change inthe keyword volume. A trending report may be generated that includes thetop ranked webpage for each keyword and one or more other webpagesincluding the keyword.

The reports may include a function that enables display of informationfor a particular date and/or time. For example, a particular date in thepast may be selected and data from that date may correspond to thatdate.

The report may also include an option to export the data in to anotherformat, such as, a text file, a comma-separated values (CSV) file, orany other type of file. The exported data may include all or a portionof the data shown in the electronic report. The exported data mayadditional include, for example, a number of visits, a number of webpageviews, conversations and/or orders within a predetermined time period.The reports may also be configured into one or more at-a-glance views orso-called “dashboards.” The keyword link between social mediacorrespondence and webpages may be used to generate specificrecommendations to leverage those webpages and drive engagement andrevenue on the social media. Such recommendations will be tied to thekeyword and the webpage.

Providing customers with such tools for optimizing social media effortsand campaigns enables the customers to maximize engagement, traffic andconversions through the social media, such as Twitter.

FIG. 2 illustrates an embodiment of a method 200 for increasing socialmedia engagement. The method 200 can be implemented in the social mediaoptimization system 100 a or 100 b of FIG. 1A or 1B, for instance. Themethod 200 may include identifying one or more SEO keywords from awebpage of an entity at block 210. In some embodiments, identifying oneor more SEO keywords from the webpage of the entity can include crawlingthe website of the entity, obtaining SEO data from the website, andidentifying the SEO keywords. The SEO keywords can include any brandednames of the entity or other words or string of words that areassociated with the entity, product names produced by the entity,product categories, relevant search terms, general topics, and otherwords or strings of words used in SEO.

The method 200 can further include identifying social mediacorrespondence from social media webpages that reference the SEOkeywords at block 220. In some embodiments, identifying social mediacorrespondence from the social media webpage can include crawling thesocial media webpage, obtaining SEO data from the webpage, and analyzingsocial correspondence located on the social media webpage for referencesto the previously identified SEO keywords. In some embodiments, the SEOkeywords referenced more often in the social media correspondences mayby noted. Additionally or alternately, the frequency that SEO keywordsare referenced in social media correspondence may be determined andtracked to create a moving average of the number of references. If thenumber of social media correspondences that reference a particular SEOkeyword is above or below the moving average of number of references forthat SEO keyword or string of keywords, the SEO keyword or string ofkeywords may be noted.

In some embodiments, the method 200 may further include identifyingsocial media participants with higher than average social mediaparticipation. Social media participants with higher than average socialmedia participation may be considered influential participates. Thesesocial media participants may be identified based on one or morefactors. Factors may include the number of social media participantfollowers, the number of social media correspondences produced, andother factors.

In some embodiments, the method 200 may further include identifyingspecific social media participants that have provided input to thesocial media with respect to the social media correspondence referencingthe SEO keywords.

The method 200 can further include recommending material, related towebpages that contain the SEO keywords referenced in social mediacorrespondence, for engagement in the social media at block 230.Engagement in the social media can include contributing to the socialmedia by producing social media correspondence, distributing socialmedia correspondence, or some other contribution. In some embodiments,the material related to all SEO keywords referenced in the social mediacorrespondence can be used to engage in the social media. Additionallyor alternately, only material related to SEO keywords that are above themoving average for the number of social media correspondences thatreference the SEO keywords can be used to engage in the social media.Additionally or alternately, only material related to SEO keywords thatare below the moving average for the number of social mediacorrespondences that reference the SEO keywords are used to engage inthe social media. Additionally or alternately, only material related toan SEO keyword with the highest number of references in the social mediacorrespondence or a predetermined percentage of SEO keywords with thehighest number of references is used to engage in the social media. Insome embodiments, the material related to the SEO keywords is thematerial from a webpage from which the SEO keywords are derived.

Additionally or alternately, the method 200 can include recommendingthat social media participants that have provided social mediacorrespondence referencing the SEO keywords be engaged with materialrelated to the SEO keywords. Social media participants can be engaged bysending the social media participants new social media correspondence,replying to social media correspondence produced by the social mediaparticipants, or otherwise engaging with the social media participantsthrough the social media. Additionally or alternately, the method 200can include recommending that social media participants with higher thanaverage social media participation be engaged with material related tothe SEO keywords that the social media participants have previouslyincluded in their social media correspondence.

Additionally or alternately, the method 200 can include recommending thesuggestion of new or additional content for a webpage of a user relatedto SEO keywords that have been identified in social mediacorrespondence.

In some embodiments, the method may further include providing an entitywith data concerning the number of SEO keywords referenced in the socialmedia correspondence over a period. The data can come in the form of areport with one or more images, charts, graphs, or other display.Additionally or alternately, the entity can be provided with dataconcerning the social media correspondences that reference a certain SEOkeyword, any SEO keywords, or a combination of SEO keywords over aperiod.

An example of the method 200 is as follows. An entity, such as a shoestore may have a website with webpages that display and offer shoes forsale. The webpage may be crawled and SEO keywords, such as the brand ofthe shoes and other words such as, shoe, performance, running, andothers may be identified. The webpages of the social media may also becrawled. For example, all of the webpages of the website TWITTER may becrawled, and social media correspondence, such as, a TWEET, may beidentified and analyzed to identify SEO keywords within the social mediacorrespondence. A recommendation may be made to the shoe store to engagein the social media by generating and posting TWEETS includinginformation about the shoes, such as a sale, benefits of the shoes, orother material, based on the SEO keywords that were identified in thesocial media correspondence.

Some embodiments disclosed herein include a computer program producthaving computer-executable instructions for causing a computing systemhaving the computer program product to perform a computing method of thecomputer-executable instructions for improving SEO of social mediawebpages of an entity. The computing method can be any method describedherein as performed by a computing system. The computer program productcan be located on a computer memory device, which may be removable orintegrated with the computing system.

Some embodiments include a computing system capable of performing themethods described herein. As such, the computing system can include amemory device that has the computer-executable instructions forperforming the method.

In some embodiments, a computing device, such as a computer or memorydevice of a computer, can include an analytic module, determinationmodule, and reporting module. The analytic module, determination module,and reporting module can be configured to perform any of the methodsdescribed herein. Also, the analytic module, determination module, andreporting module can be combined into a single module or on a singleplatform.

The computer program product can include one or more algorithms forperforming any of the methods of any of the claims. The computer programproduct can include one or more algorithms for performing any of themethods of any of the claims.

One skilled in the art will appreciate that, for this and otherprocesses and methods disclosed herein, the functions performed in theprocesses and methods may be implemented in differing order.Furthermore, the outlined steps and operations are only provided asexamples, and some of the steps and operations may be optional, combinedinto fewer steps and operations, or expanded into additional steps andoperations without detracting from the essence of the disclosedembodiments. It should also be recognized that any module or componentdescribed herein can implement the functionalities associated with thename of the module or component.

The present disclosure is not to be limited in terms of the particularembodiments described in this application, which are intended asillustrations of various aspects. Many modifications and variations canbe made without departing from its spirit and scope, as will be apparentto those skilled in the art. Functionally equivalent methods andapparatuses within the scope of the disclosure, in addition to thoseenumerated herein, will be apparent to those skilled in the art from theforegoing descriptions. Such modifications and variations are intendedto fall within the scope of the appended claims. The present disclosureis to be limited only by the terms of the appended claims, along withthe full scope of equivalents to which such claims are entitled. It isalso to be understood that the terminology used herein is for describingparticular embodiments only, and is not intended to be limiting.

In an illustrative embodiment, any of the operations, processes, etc.described herein can be implemented as computer-readable instructionsstored on a computer-readable medium. The computer-readable instructionscan be executed by a processor of a mobile unit, a network element,and/or any other computing device.

There is little distinction left between hardware and softwareimplementations of aspects of systems; the use of hardware or softwareis generally (but not always, in that in certain contexts the choicebetween hardware and software can become significant) a design choicerepresenting cost vs. efficiency tradeoffs. There are various vehiclesby which processes and/or systems and/or other technologies describedherein can be effected (e.g., hardware, software, and/or firmware), andthat the preferred vehicle will vary with the context in which theprocesses and/or systems and/or other technologies are deployed. Forexample, if an implementer determines that speed and accuracy areparamount, the implementer may opt for a mainly hardware and/or firmwarevehicle; if flexibility is paramount, the implementer may opt for amainly software implementation; or, yet again alternatively, theimplementer may opt for some combination of hardware, software, and/orfirmware.

The foregoing detailed description has set forth various embodiments ofthe processes via the use of block diagrams, flowcharts, and/orexamples. Insofar as such block diagrams, flowcharts, and/or examplescontain one or more functions and/or operations, it will be understoodby those within the art that each function and/or operation within suchblock diagrams, flowcharts, or examples can be implemented, individuallyand/or collectively, by a wide range of hardware, software, firmware, orvirtually any combination thereof. In some embodiments, several portionsof the subject matter described herein may be implemented viaApplication Specific Integrated Circuits (ASICs), Field ProgrammableGate Arrays (FPGAs), digital signal processors (DSPs), or otherintegrated formats. However, those skilled in the art will recognizethat some aspects of the embodiments disclosed herein, in whole or inpart, can be equivalently implemented in integrated circuits, as one ormore computer programs running on one or more computers (e.g., as one ormore programs running on one or more computer systems), as one or moreprograms running on one or more processors (e.g., as one or moreprograms running on one or more microprocessors), as firmware, or asvirtually any combination thereof, and that designing the circuitryand/or writing the code for the software and or firmware would be wellwithin the skill of one of skill in the art in light of this disclosure.In addition, those skilled in the art will appreciate that themechanisms of the subject matter described herein are capable of beingdistributed as a program product in a variety of forms, and that anillustrative embodiment of the subject matter described herein appliesregardless of the particular type of signal bearing medium used toactually carry out the distribution. Examples of a signal bearing mediuminclude, but are not limited to, the following: a recordable type mediumsuch as a floppy disk, a hard disk drive, a CD, a DVD, a digital tape, acomputer memory, etc.; and a transmission type medium such as a digitaland/or an analog communication medium (e.g., a fiber optic cable, awaveguide, a wired communications link, a wireless communication link,etc.).

Those skilled in the art will recognize that it is common within the artto describe devices and/or processes in the fashion set forth herein,and thereafter use engineering practices to integrate such describeddevices and/or processes into data processing systems. That is, at leasta portion of the devices and/or processes described herein can beintegrated into a data processing system via a reasonable amount ofexperimentation. Those having skill in the art will recognize that atypical data processing system generally includes one or more of asystem unit housing, a video display device, a memory such as volatileand non-volatile memory, processors such as microprocessors and digitalsignal processors, computational entities such as operating systems,drivers, graphical user interfaces, and applications programs, one ormore interaction devices, such as a touch pad or screen, and/or controlsystems including feedback loops and control motors (e.g., feedback forsensing position and/or velocity; control motors for moving and/oradjusting components and/or quantities). A typical data processingsystem may be implemented utilizing any suitable commercially availablecomponents, such as those generally found in datacomputing/communication and/or network computing/communication systems.

The herein described subject matter sometimes illustrates differentcomponents contained within, or connected with, different othercomponents. It is to be understood that such depicted architectures aremerely exemplary, and that in fact many other architectures can beimplemented which achieve the same functionality. In a conceptual sense,any arrangement of components to achieve the same functionality iseffectively “associated” such that the desired functionality isachieved. Hence, any two components herein combined to achieve aparticular functionality can be seen as “associated with” each othersuch that the desired functionality is achieved, irrespective ofarchitectures or intermedial components. Likewise, any two components soassociated can also be viewed as being “operably connected”, or“operably coupled”, to each other to achieve the desired functionality,and any two components capable of being so associated can also be viewedas being “operably couplable”, to each other to achieve the desiredfunctionality. Specific examples of operably couplable include but arenot limited to physically mateable and/or physically interactingcomponents and/or wirelessly interactable and/or wirelessly interactingcomponents and/or logically interacting and/or logically interactablecomponents.

FIG. 3 shows an example computing device 300 that is arranged to performany of the computing methods described herein. In a very basicconfiguration 302, computing device 300 generally includes one or moreprocessors 304 and a system memory 306. A memory bus 308 may be used forcommunicating between processor 304 and system memory 306.

Depending on the desired configuration, processor 304 may be of any typeincluding but not limited to a microprocessor (μP), a microcontroller(μC), a digital signal processor (DSP), or any combination thereof.Processor 304 may include one more levels of caching, such as a levelone cache 310 and a level two cache 312, a processor core 314, andregisters 316. An example processor core 314 may include an arithmeticlogic unit (ALU), a floating point unit (FPU), a digital signalprocessing core (DSP Core), or any combination thereof. An examplememory controller 318 may also be used with processor 304, or in someimplementations memory controller 318 may be an internal part ofprocessor 304.

Depending on the desired configuration, system memory 306 may be of anytype including but not limited to volatile memory (such as RAM),non-volatile memory (such as ROM, flash memory, etc.) or any combinationthereof. System memory 306 may include an operating system 320, one ormore applications 322, and program data 324. Application 322 may includea determination application 326 that is arranged to perform thefunctions as described herein including those described with respect tomethods described herein. The determination application 326 maycorrespond to the determination module 124 of FIG. 1B, for example.Program Data 324 may include determination information 328 that may beuseful for analyzing social media correspondences located on the socialmedia webpage. In some embodiments, application 322 may be arranged tooperate with program data 324 on operating system 320.

Computing device 300 may have additional features or functionality, andadditional interfaces to facilitate communications between basicconfiguration 302 and any required devices and interfaces. For example,a bus/interface controller 330 may be used to facilitate communicationsbetween basic configuration 302 and one or more data storage devices 332via a storage interface bus 334. Data storage devices 332 may beremovable storage devices 336, non-removable storage devices 338, or acombination thereof. Examples of removable storage and non-removablestorage devices include magnetic disk devices such as flexible diskdrives and hard-disk drives (HDD), optical disk drives such as compactdisk (CD) drives or digital versatile disk (DVD) drives, solid statedrives (SSD), and tape drives to name a few. Example computer storagemedia may include volatile and nonvolatile, removable and non-removablemedia implemented in any method or technology for storage ofinformation, such as computer readable instructions, data structures,program modules, or other data.

System memory 306, removable storage devices 336 and non-removablestorage devices 338 are examples of computer storage media. Computerstorage media includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology, CD-ROM, digital versatile disks (DVD)or other optical storage, magnetic cassettes, magnetic tape, magneticdisk storage or other magnetic storage devices, or any other mediumwhich may be used to store the desired information and which may beaccessed by computing device 300. Any such computer storage media may bepart of computing device 300.

Computing device 300 may also include an interface bus 340 forfacilitating communication from various interface devices (e.g., outputdevices 342, peripheral interfaces 344, and communication devices 346)to basic configuration 302 via bus/interface controller 330. Exampleoutput devices 342 include a graphics processing unit 348 and an audioprocessing unit 350, which may be configured to communicate to variousexternal devices such as a display or speakers via one or more A/V ports352. Example peripheral interfaces 344 include a serial interfacecontroller 354 or a parallel interface controller 356, which may beconfigured to communicate with external devices such as input devices(e.g., keyboard, mouse, pen, voice input device, touch input device,etc.) or other peripheral devices (e.g., printer, scanner, etc.) via oneor more I/O ports 358. An example communication device 346 includes anetwork controller 360, which may be arranged to facilitatecommunications with one or more other computing devices 362 over anetwork communication link via one or more communication ports 364.

The network communication link may be one example of a communicationmedia. Communication media may generally be embodied by computerreadable instructions, data structures, program modules, or other datain a modulated data signal, such as a carrier wave or other transportmechanism, and may include any information delivery media. A “modulateddata signal” may be a signal that has one or more of its characteristicsset or changed in such a manner as to encode information in the signal.By way of example, and not limitation, communication media may includewired media such as a wired network or direct-wired connection, andwireless media such as acoustic, radio frequency (RF), microwave,infrared (IR) and other wireless media. The term computer readable mediaas used herein may include both storage media and communication media.

Computing device 300 may be implemented as a portion of a small-formfactor portable (or mobile) electronic device such as a cell phone, apersonal data assistant (PDA), a personal media player device, awireless web-watch device, a personal headset device, an applicationspecific device, or a hybrid device that include any of the abovefunctions. Computing device 300 may also be implemented as a personalcomputer including both laptop computer and non-laptop computerconfigurations. The computing device 300 can also be any type of networkcomputing device. The computing device 300 can also be an automatedsystem as described herein.

The embodiments described herein may include the use of a specialpurpose or general-purpose computer including various computer hardwareor software modules.

Embodiments within the scope of the present invention also includecomputer-readable media for carrying or having computer-executableinstructions or data structures stored thereon. Such computer-readablemedia can be any available media that can be accessed by a generalpurpose or special purpose computer. By way of example, and notlimitation, such computer-readable media can comprise RAM, ROM, EEPROM,CD-ROM or other optical disk storage, magnetic disk storage or othermagnetic storage devices, or any other medium which can be used to carryor store desired program code means in the form of computer-executableinstructions or data structures and which can be accessed by a generalpurpose or special purpose computer. When information is transferred orprovided over a network or another communications connection (eitherhardwired, wireless, or a combination of hardwired or wireless) to acomputer, the computer properly views the connection as acomputer-readable medium. Thus, any such connection is properly termed acomputer-readable medium. Combinations of the above should also beincluded within the scope of computer-readable media.

Computer-executable instructions comprise, for example, instructions anddata that cause a general-purpose computer, special purpose computer, orspecial purpose processing device to perform a certain function or groupof functions. Although the subject matter has been described in languagespecific to structural features and/or methodological acts, it is to beunderstood that the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing the claims.

As used herein, the term “module” or “component” can refer to softwareobjects or routines that execute on the computing system. The differentcomponents, modules, engines, and services described herein may beimplemented as objects or processes that execute on the computing system(e.g., as separate threads). While the system and methods describedherein are preferably implemented in software, implementations inhardware or a combination of software and hardware are also possible andcontemplated. In this description, a “computing entity” may be anycomputing system as previously defined herein, or any module orcombination of modulates running on a computing system.

With respect to the use of substantially any plural and/or singularterms herein, those having skill in the art can translate from theplural to the singular and/or from the singular to the plural as isappropriate to the context and/or application. The varioussingular/plural permutations may be expressly set forth herein for sakeof clarity.

It will be understood by those within the art that, in general, termsused herein, and especially in the appended claims (e.g., bodies of theappended claims) are generally intended as “open” terms (e.g., the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.). It will be further understood by those within the art that if aspecific number of an introduced claim recitation is intended, such anintent will be explicitly recited in the claim, and in the absence ofsuch recitation no such intent is present. For example, as an aid tounderstanding, the following appended claims may contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimrecitations. However, the use of such phrases should not be construed toimply that the introduction of a claim recitation by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim recitation to embodiments containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should be interpreted to mean “at least one”or “one or more”); the same holds true for the use of definite articlesused to introduce claim recitations. In addition, even if a specificnumber of an introduced claim recitation is explicitly recited, thoseskilled in the art will recognize that such recitation should beinterpreted to mean at least the recited number (e.g., the barerecitation of “two recitations,” without other modifiers, means at leasttwo recitations, or two or more recitations). Furthermore, in thoseinstances where a convention analogous to “at least one of A, B, and C,etc.” is used, in general such a construction is intended in the senseone having skill in the art would understand the convention (e.g., “asystem having at least one of A, B, and C” would include but not belimited to systems that have A alone, B alone, C alone, A and Btogether, A and C together, B and C together, and/or A, B, and Ctogether, etc.). In those instances where a convention analogous to “atleast one of A, B, or C, etc.” is used, in general such a constructionis intended in the sense one having skill in the art would understandthe convention (e.g., “a system having at least one of A, B, or C” wouldinclude but not be limited to systems that have A alone, B alone, Calone, A and B together, A and C together, B and C together, and/or A,B, and C together, etc.). It will be further understood by those withinthe art that virtually any disjunctive word and/or phrase presenting twoor more alternative terms, whether in the description, claims, ordrawings, should be understood to contemplate the possibilities ofincluding one of the terms, either of the terms, or both terms. Forexample, the phrase “A or B” will be understood to include thepossibilities of “A” or “B” or “A and B.”

In addition, where features or aspects of the disclosure are describedin terms of Markush groups, those skilled in the art will recognize thatthe disclosure is also thereby described in terms of any individualmember or subgroup of members of the Markush group.

As will be understood by one skilled in the art, for any and allpurposes, such as in terms of providing a written description, allranges disclosed herein also encompass any and all possible subrangesand combinations of subranges thereof. Any listed range can be easilyrecognized as sufficiently describing and enabling the same range beingbroken down into at least equal halves, thirds, quarters, fifths,tenths, etc. As a non-limiting example, each range discussed herein canbe readily broken down into a lower third, middle third and upper third,etc. As will also be understood by one skilled in the art all languagesuch as “up to,” “at least,” and the like include the number recited andrefer to ranges that can be subsequently broken down into subranges asdiscussed above. Finally, as will be understood by one skilled in theart, a range includes each individual member. Thus, for example, a grouphaving 1-3 cells refers to groups having 1, 2, or 3 cells. Similarly, agroup having 1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells,and so forth.

From the foregoing, it will be appreciated that various embodiments ofthe present disclosure have been described herein for purposes ofillustration, and that various modifications may be made withoutdeparting from the scope and spirit of the present disclosure.Accordingly, the various embodiments disclosed herein are not intendedto be limiting, with the true scope and spirit being indicated by thefollowing claims. All references recited herein are incorporated hereinby specific reference in their entirety.

What is claimed is:
 1. A method, the method comprising: identifyingsearch engine optimization keywords associated with an entity;identifying social media correspondence from social media referencingthe search engine optimization keywords; designating one or more of thesearch engine optimization keywords as selected keywords based on thesocial media correspondence; requesting search results from a searchengine that result from a search of the selected keywords on the searchengine; identifying one or more non-social media webpages that areassociated with the entity and that are included in the search results;and generating an electronic notification for sending to the entity, theelectronic notification recommending material for engagement in thesocial media, the material including information located on theidentified one or more non-social media webpages.
 2. The method of claim1, wherein the material includes the selected keywords.
 3. The method ofclaim 1, further comprising recommending creation of content related tocontent on the one or more non-social media webpages.
 4. The method ofclaim 1, wherein identifying social media correspondence comprisesidentifying the social media correspondence obtained from at least onemobile device.
 5. The method of claim 1, further comprising ranking theidentified one or more non-social media webpages based on at least oneof search engine result location of the identified non-social mediawebpages, traffic on the identified one or more non-social mediawebpages, conversions generated by the identified one or more non-socialmedia webpages, conversion rate of the identified one or more non-socialmedia webpages, and revenues generated by the identified one or morenon-social media webpages, wherein the material from the electronicnotification includes information from the identified non-social mediawebpages that are highly ranked.
 6. The method of claim 1, wherein theone or more of the search engine optimization keywords are designated asselected keywords based on a frequency that the selected keywords areincluded in the social media correspondence.
 7. The method of claim 1,wherein the one or more of the search engine optimization keywords aredesignated as selected keywords based on the selected keywords beingincluded in the social media correspondence provided by a social mediaparticipant with higher than average social media participation.
 8. Themethod of claim 1, wherein the electronic notification furtherrecommends that the identified one or more non-social media webpages beoptimized.
 9. The method of claim 1, further comprising determining oneor more webpages associated with the entity that are shared in theidentified social media correspondence, wherein the material recommendedfor engagement includes information located on the one or more webpagesassociated with the entity that are shared in the identified socialmedia correspondence.
 10. A non-transitory computer-readable storagemedium whose contents, when executed by a processor, cause the processorto perform operations including: identifying search engine optimizationkeywords associated with an entity; identifying social mediacorrespondence from social media referencing the search engineoptimization keywords; designating one or more of the search engineoptimization keywords as selected keywords based on the social mediacorrespondence; requesting search results from a search engine thatresult from a search of the selected keywords on the search engine;identifying one or more non-social media webpages that are associatedwith the entity and that are included in the search results; andgenerating an electronic notification for sending to the entity, theelectronic notification recommending material for engagement in thesocial media, the material including information located on theidentified one or more non-social media webpages.
 11. The non-transitorycomputer-readable storage medium of claim 10, wherein the operationsfurther comprise ranking the identified one or more non-social mediawebpages based on at least one of search engine result location of theidentified non-social media webpages, traffic on the identified one ormore non-social media webpages, conversions generated by the identifiedone or more non-social media webpages, conversion rate of the identifiedone or more non-social media webpages, and revenues generated by theidentified one or more non-social media webpages, wherein the materialfrom the electronic notification includes information from theidentified non-social media webpages that are highly ranked.
 12. Thenon-transitory computer-readable storage medium of claim 10, wherein thematerial includes the selected keywords.
 13. The non-transitorycomputer-readable storage medium of claim 10, wherein the operationsfurther comprise recommending creation of content related to content onthe one or more non-social media webpages.
 14. The non-transitorycomputer-readable storage medium of claim 10, wherein identifying socialmedia correspondence comprises identifying the social mediacorrespondence obtained from at least one mobile device.
 15. Thenon-transitory computer-readable storage medium of claim 10, wherein theone or more of the search engine optimization keywords are designated asselected keywords based on a frequency that the selected keywords areincluded in the social media correspondence.
 16. The non-transitorycomputer-readable storage medium of claim 10, wherein the one or more ofthe search engine optimization keywords are designated as selectedkeywords based on the selected keywords being included in the socialmedia correspondence provided by a social media participant with higherthan average social media participation.
 17. The non-transitorycomputer-readable storage medium of claim 10, wherein the electronicnotification further recommends that the identified one or morenon-social media webpages be optimized.
 18. The non-transitorycomputer-readable storage medium of claim 10, wherein the operationsfurther include determining one or more webpages associated with theentity that are shared in the identified social media correspondence,wherein the material recommended for engagement includes informationlocated on the one or more webpages associated with the entity that areshared in the identified social media correspondence.